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Performance of the Angle Labor Pain Questionnaire During Initiation of Epidural Analgesia in Early Active Labor

2017· article· en· W2745811322 on OpenAlexaff
Pamela Angle, Christine Kurtz Landy, Jasmine Djordjevic, Jon Barrett, Alanna Kibbe, Saiena Sriparamananthan, Y. Lee, Lydia Hamata, Pearl Zaki, Alex Kiss

Bibliographic record

VenueObstetric Anesthesia Digest · 2017
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsLabor painMedicineChildbirthVisual analogue scaleRating scaleScale (ratio)AnesthesiaPhysical therapyPregnancyDevelopmental psychologyPsychologyCartography

Abstract

fetched live from OpenAlex

( Anesth Analg . 2016;123(6):1546–1553) The Angle Labor Pain Questionnaire (A-LPQ) was developed to overcome difficulties associated with assessing women’s pain experiences during childbirth, experiences which are multidimensional but often measured using unidimensional and unreliable tools (eg, visual analog scale, numeric rating scale, etc.).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.534

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.235
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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